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Fig 1.

A distributed architecture implementation of spatial-temporal k-anonymity.

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Fig 1 Expand

Table 1.

A sample of SingleRules.

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Table 1 Expand

Fig 2.

Workflow for generating anonymity datasets based on the NOSTK method.

(A)The main flow chart. (B)The sub-flow chart for checking the current grid cell and selecting a generalization principle. (C)The sub-flow chart for sorting searched neighbor grid cells based on selected generalization principles.

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Fig 3.

A scenario that the current grid cell is an nPSSR grid cell.

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Fig 4.

Searching grid cells near C5 in a counterclockwise direction.

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Fig 4 Expand

Fig 5.

The generated cloaking region based on the avoidance principle and the minimum generalization principle.

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Table 2.

The grid cells sorted in a descending order.

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Table 2 Expand

Fig 6.

A scenario that the current grid cell is a PSSR grid cells but not a PSR grid cell.

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Fig 7.

The generated cloaking region based on the avoidance principle and the normal generalization principle.

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Table 3.

The grid cells filtered out PSSR grid cells and PSR grid cells.

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Table 3 Expand

Fig 8.

A scenario that the current grid cell is a PSR grid cell.

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Fig 8 Expand

Fig 9.

The generated cloaking region based on the avoidance principle and the maximum generalization principle.

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Table 4.

The grid cells sorted in an ascending order.

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Table 4 Expand

Table 5.

Batches of sequences of cloaking regions with K = 10~18.

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Table 5 Expand

Table 6.

Sequence rules mined from Table 5 and specified privacy-sensitive rules.

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Table 6 Expand

Fig 10.

Hiding sensitive rules ratios change with data expansion using the NOSTK method.

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Fig 11.

Hiding sensitive rules ratios change with data expansion using the tSTK method.

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Fig 12.

Newly generated sensitive rules ratios change with data expansion using the NOSTK method.

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Fig 13.

Newly generated sensitive rules ratios change with data expansion using the tSTK method.

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Fig 14.

Non-sensitive rules variation ratios change with data expansion using the NOSTK method.

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Fig 15.

Non-sensitive rules variation ratios change with data expansion using the tSTK method.

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Fig 16.

Non-sensitive rules variation ratios difference between the NOSTK method and the tSTK method.

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Fig 17.

Hiding sensitive rules ratios change with K values for different incremental combinations.

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Fig 18.

Newly generated sensitive rules ratios change with K values for different incremental combinations.

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Fig 19.

Non-sensitive rules variation ratios change with K values for different incremental combinations.

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Fig 20.

Mixed measure values change with K values for different incremental combinations.

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